The present invention relates to a method for the dynamic matrix control of a process in a pulp mill, namely a Kamyr digester.
Dynamic matrix control (DMC) methods are as old as the art. For example, the DMC methods disclosed in prior U.S. Pat. Nos. 4,349,869 and 4,616,308 comprise MV control algorithms which use mathematical models. These algorithms calculate values of one or more manipulable process variables to maintain one or more controlled variables at their setpoints. The calculations involve the use of predictions for the controlled variables based on the estimated response to changes in all the independent process variables (including the manipulated variables) which affect the controlled process variables. The algorithms calculate the future values of the manipulated variables which will minimize any future deviations of the controlled variables from their setpoints. Using predictions of the effect of the independent process variables on the controlled variables provides feedforward action for the control system and also minimizes the effects of interactions between the independent process variables which are manipulated to maintain the controlled variables at their setpoints.
The prior art methods of dynamic matrix control use periodic measurements of the controlled variable to correct the predictions used to calculate new values for the manipulated variables. The most recent prediction of the controlled variable is adjusted so that it matches the most recent measurement of the controlled variable. This provides feedback action for the algorithms. However, the measurement processes for controlled variables in some process systems may involve significant delay periods. This is particularly true when the controlled variable is a chemical composition and the measurement process involves collecting a sample and performing a wet lab experiment to determine its composition. The use of such a delayed measurement in the known DMC systems would result in severe errors in the control calculations, particularly if the controlled variable was changing rapidly.
The prior art DMC systems also use estimates of the response of the controlled variable to step changes in the independent variables. These are usually obtained by changing each independent variable while holding the others constant and recording the response of the controlled variable. However in many processes it is not possible to obtain step responses in this manner; the step responses must be obtained by examining a great deal of process data and estimating the step responses. Such estimates may be in error by as much as 20% due to process noise and unmeasured disturbances. This can also lead to severe errors in the control calculations, especially if there are large errors in the estimates of the process deadtime (i.e. the time between when an independent variable is changed and when the dependent variable starts to respond).
Finally, prior art methods of DMC may also use step response estimates of all the independent process variables which affect the controlled variable. The independent variables which are not manipulated are called disturbance variables. Using the step response information from these variables to calculate the predicted behavior of the controlled variable provides feedforward action for the control system. However, if there is a large deadtime in the step response for the manipulated variables and/or the disturbance variables, changes in the disturbance variables can lead to considerable errors in the controlled variable before the effect of changes in the manipulated variables drive the controlled variable back to its setpoint.
In contrast to the above, it is an object of the present invention to provide a method of DMC which provides the advantages of the feedforward and feedback aspects of the prior art methods yet addresses the problems inherent with deadtime in the feedforward action and delays caused by lengthy measurement processes.